In the design of a process plant, such as, for example, an oil and gas facility, a gas cleaning plant, a carbon dioxide capture facility, a liquefied natural gas (LNG) plant, an oil refinery, or a petrochemical facility (e.g., an ethylene plant), companies need to make major multi-million dollar investment decisions about the most appropriate capacity, location, and functionality of the facility, typically with very limited information, particularly at preliminary stages of the design. There are many potential configuration and design options, making it difficult to identify viable options and to compare them on a consistent basis, so that the optimal design can be selected for the best match to business criteria and operational constraints, and for a sound economic return on investment. At present, engineers and business managers address this problem by a variety of short-cut design methods and practices, standards, and approximations for design selection. These methods have been encapsulated in software applications, linear programming (LP) models, and tools such as, for example, Microsoft EXCEL®. Alternatively, companies base their assessments on large libraries of previous typical designs and costing databases. Templates, which can be re-used and edited by the user, are typically used for sub-processes. The use of templates is generally impractical for entire processes, due to large variations in process conditions and constraints for each specific process.
At present, the design of process facilities is becoming more complex, due to many factors such as, for example, more complex feedstocks, higher feed pressures and temperatures, the presence of trace elements, tighter product quality specifications, tighter environmental and safety constraints, and more volatile market conditions and global economic factors. The added complexity increases the necessity to scrutinize design options more thoroughly earlier in the design cycle, in order to accurately assess project risks and avoid design rework at later stages of the design cycle or the procurement of inappropriate or incorrect equipment.
Present design methods are not sufficiently rigorous in taking into account the underlying thermodynamics, physical properties, and unit operation and equipment design methods to meet the increasing technical complexity of modern process design and the increasing scrutiny of technical risks. Rigorous process simulators, which could provide the level of detail required for modern process design, are typically only used to validate the final few selected design alternatives, in part because rigorous process simulators typically require input of detailed process data. Such data is generally limited or not available at the early stages of process design. The user must either obtain the input data or apply an engineering assumption based on the user's experience or an industry or company guideline. Furthermore, the manual configuration by the user of plant topology and connectivity is quite time consuming, making it impractical to create a rigorous process simulation model of each potential design alternative.
Therefore, there is a need for a pre-screening and configuration engine for a rigorous process simulator.